References¶
Paszke, A, et al. 2019, PyTorch: An Imperative Style, High-Performance Deep Learning Library, Neural Information Processing Systems, no. 32, pp. 8024–8035, accessed 10 September 2021, article URL.
Lane, H, Howard, C and Hapke, H 2019, Natural Language Processing in Action, Manning Publications, Shelter Island, NY, USA.
Pennington, J, Socher, R and Manning, CD 2014, GloVe: Global Vectors for Word Representation, website.
Graves, A 2011, Practical Variational Inference for Neural Networks, Advances in Neural Information Processing Systems 24, pp. 2348-2356, accessed 7 October 2021, article URL.
Glassner, A 2021, Deep Learning: A Visual Approach, No Starch Press, San Francisco, Ca, USA.
He, K, Zhang, X, Ren, S & Sun, J 2015, Delving deep into rectifiers: Surpassing human-level performance on imagenet classification, Proceedings of the IEEE International Conference on Computer Vision, pp. 1026-1034, accessed 10 September 2021, article URL.
Graves, A & Schmidhuber J 2005, Framewise Phoneme Classification with Bidirectional LSTM Netwroks, Neural Networks, vol 18, no. 5-6, pp. 602-610, accessed 10 September 2021, article URL.
Pointer, I 2019, Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications, O’Reilly Media, Sebastopol, CA, USA.